Published Paper Details:

: Skin malignancy is the most well-known reason for death among people. Skin disease is unusual development of skin cells frequently creates on body presented to the daylight, yet can happen anyplace on the body. Since this cancer is visible on the skin, it is potentially detectable at a very early stage when it is curable. With the new innovation, early identification of skin growth is conceivable at beginning stage. Early technique for analysis skin growth location is Biopsy technique [1]. It is finished by evacuating skin cells and that example goes to different research centre testing. It is difficult and tedious process. In this paper we present Particle Swarm Optimization (PSO) for segmentation and Hidden Markov Model (HMM) for the classification of skin lesions. The input to the system is the skin lesion image and it goes under different pre-processing method for noise removal and image enhancement. At that point the picture is experienced to division utilizing PSO strategy. A few highlights of picture must be extricated utilizing GLCM system. These highlights are given as the contribution to classifier. Hidden Markov Model (HMM) is utilized for characterization reason. It conclude about the presence of skin cancer or not.